A Beta-GAM hidden Markov model for proportion time series identifies latent regimes and smooth nonlinear covariate effects via penalized EM estimation and information-criterion state selection.
Methodology and Computing in Applied Probability , year =
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A Beta-GAM Hidden Markov Model for Proportion Time Series
A Beta-GAM hidden Markov model for proportion time series identifies latent regimes and smooth nonlinear covariate effects via penalized EM estimation and information-criterion state selection.